Robust methods in bioequivalence assay; preliminary results.

Abstract

The aim of this study is to compare four statistical methods for outlier identification in Bioequivalence tests. The methods are based in four confidence intervals, 'parametric','non- parametric','robust with the asymptotic distribution of the M-estimator' and 'robust with the bootstrap distribution'. The drug we used was Diltiazen, in a two sequence randomized crossover study design. The pharmacokinetic parameters measured were the area under the plasma concentration curve (AUC), and the peak drug concentration (CMAX). Time to peak drug concentration (TMAX), was not used here in order to separate the efficiency of the methods from the efficiency of the measurements. The methods were applied to simulated and experimental data. We made two simulations, one with normal data and another one with outliers data. When simulating normal data all methods showed similar profiles and high power. On the contrary, when simulating experiments with outliers data, the parametric method showed low power, whereas robust methods showed just a slight decrement in power. When we analyzed experimental data of AUC, if we used the parametric method (recommended by U.S.P), we were not able to conclude Bioequivalence, but with the other methods, this was possible. This disagreement between parametric and robust procedures was a sign of outliers data. We conclude that the robust methods in bioequivalence assays help us in the identification of outliers as observations with weight equal zero.